About halfway through a pregnancy, an expectant mother may notice the first symptoms of some serious complications. For instance, abnormally high blood pressure and dark urine starting at 20 weeks is a sign of preeclampsia, while excessive thirst and frequent urination beginning around 24 weeks could indicate gestational diabetes.  

Medical providers can use blood tests to diagnose these conditions and others when symptoms appear, but at that point, “the damage has already been done,” said Surendra Sharma, an obstetrician and molecular biologist at the University of Texas Medical Branch. Not only do these complications affect the health and well-being of the mother and her child during pregnancy, but they can cause adverse consequences for both after birth as well (1,2).

Intervening before symptoms start would likely lead to better outcomes, and creating a reliable screening tool that allows medical providers to identify women who are in the process of developing serious complications is the first step towards that goal. To that end, Carlos Palma and a team of researchers at the University of Queensland have focused on placental extracellular vesicles (EVs). 

Cells throughout the body regularly release EVs, which are tiny packets of molecules that can offer a snapshot of their originator’s current status. A lot is still unknown about the precise relationship between health and EVs for various tissues and cell types, but researchers have linked disease and distress to changes in both the composition and the quantity of EVs released by the placenta (3). Focusing on the latter, Palma’s team developed a sensor to quantify placental EVs (4).

First, Palma’s team needed to identify a reliable pair of biomarkers for placental EVs. They took blood plasma samples from 201 pregnant women at 13 weeks into their pregnancies, on average. Half of the women had normal pregnancies, and the other half developed a serious complication. These included preeclampsia, gestational diabetes, preterm birth, and others. 

After isolating the EVs from the maternal plasma samples, Palma’s team measured the total amounts of multiple proteins they knew to be associated with the placenta or with EVs in general. Then, the researchers trained an algorithm that used each of those protein quantities to distinguish the women who developed pregnancy complications from the women who did not. The algorithm was most accurate when the researchers fed it information about placental alkaline phosphatase (PLAP) and cluster of differentiation 9 (CD9), which is a general biomarker for EVs of all kinds.

Because PLAP and CD9 quantities were their strongest predictors for pregnancy complications, Palma’s team created a sensor to isolate and detect EVs bearing those biomarkers. To do that, they synthesized tiny magnetic beads equipped with flower-like petals covered in PLAP antibodies. The materials they used to synthesize the beads also gave the metallic structures enzymatic properties. Specifically, the beads could turn the dye tetramethylbenzidine (TMB) from colorless to blue without the need for biological enzymes that would normally catalyze this reaction.

After incubating the beads in blood plasma samples, the researchers used a magnet to isolate them with the PLAP-presenting EVs attached. Then, Palma and his team dripped the solution of beads and EVs onto a glass surface covered in CD9 antibodies and washed away all the beads without EVs. Thus, the number of beads left on the glass surface closely approximated the number of placental EVs in the blood plasma sample.

Finally, they added TMB to the glass surface and watched as the beads turned it blue. The deeper the blue, the more EVs were in the sample. They also measured the color change with a spectrophotometer, fed the values into a predictive algorithm, and found that their sensor was particularly accurate when identifying women that would go on to develop gestational diabetes.

Andy Powell, a biochemist at Liverpool John Moores University who was not involved in the study, thought the idea behind the technology was great. Comparing it to the pregnancy test, he said, “They’re trying to almost make this as usable as that, but for blood instead of urine.” He especially appreciated the decision to use an artificial metallic enzyme for the color change rather than a protein that might be less stable in storage. 

But both Powell and his colleague at Liverpool John Moores University, Iain Dykes, found it a little surprising that Palma’s team had such success with the biomarkers they chose, given that neither is particularly specific to any one disease. “They haven’t really looked in detail at what signals these EVs might be carrying,” said Dykes. 

It’s a very wonderful starting point. … We need to go to the finish line. 
- Surendra Sharma, University of Texas Medical Branch

Instead, Palma’s team focused on the quantity of placental EVs. Sharma, who was also not involved in the study, was skeptical of this diagnostic strategy because he’s seen mixed results when other groups have sought to link a threshold amount of EVs to different diseases. That variability in diagnostic success could be especially problematic if a sensor based on the work of Palma’s team went to market as a general pregnancy complication detector.

Instead, Sharma would like to see if Palma’s team could find disease-specific biomarkers that would allow them to adapt their technology to test for preeclampsia, gestational diabetes, or another complication. “It’s a very wonderful starting point,” he said. “We need to go to the finish line.”

References

1. Reece, E.A. The fetal and maternal consequences of gestational diabetes mellitus. J Matern Fetal Neonatal Med  23, 199-203 (2010).
2. Turbeville, H.R. & Sasser, J.M. Preeclampsia beyond pregnancy: long-term consequences for mother and child. Am J Physiol  318, F1315-F1326 (2020).
3. Tong, M. & Chamley, L.W. Placental extracellular vesicles and feto-maternal communications. Cold Spring Harb Perspect Med  5, a023028 (2015).
4. Palma, C. et al.  Rapid and high-sensitivity screening of pregnancy complications by profiling circulating placental extracellular vesicles. Sci Adv  11, eadr4074 (2025).